Intro To Deep Learning
Leon Noel
RC Ascend
Agenda
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Questions?
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Let's Talk - Learning
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Learn - What is Machine, Deep, Ect Learning?
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Learn - What is a model?
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Learn - Bird or Not Model?
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Do - Read Paper + Watch 1.2
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Homework - Week 01 Fast.ai
Questions
About last class or life
Resetting Forgetting Curve
https://www.pearsoned.com/three-simple-research-based-ways-to-ace-a-test
Active Recall & Spaced Repetition
Ali Abdaal: https://youtu.be/Z-zNHHpXoMM
Trough Of Sorrow
Manage Frustration
Consistency
Taking Care Of Yourself
AI
A computer will do what you tell it to do.
What is artificial intelligence?
Creation of computer systems that can perform tasks typically requiring human intelligence
Classification
Prediction
DATA
Prediction
What is machine learning?
Creation of computer systems that can perform a task without be explicitly programmed to complete that task that typically requires structured data
https://www.kaggle.com/datasets/alessiocorrado99/animals10
cat
cat
cat
elephant
elephant
elephant
What is deep learning?
Creation of computer systems that can perform a task without be explicitly programmed to complete that task that typically DOES NOT require
structured data
https://www.kaggle.com/datasets/alessiocorrado99/animals10
DATA
Prediction
Training Set
Test Set
DATA
Training
Data
Test
Data
78 %
Algorithm
Algorithm
Linear Regression
Decision Tree
Manual Feature Engineering
Algorithm
Convolutional Neural Networks (CNNs)
Automatic Feature Engineering
Training
Data
Test
Data
78 %
Algorithm
Error Function
accuracy_score(prediction, test_data)Output = Model
Model by itself is just an empty brain that has not yet learned anything
Weights represent the knowledge that the model has learned from the
training data
The primary function of a model is to make predictions or classifications based on input data. The weights are what allow the model to perform this function accurately. Without weights, the model cannot process the input data correctly to produce meaningful outputs.
Model trained to recognize cars will have weights that enable it to distinguish different cars
Model + Weights = Accurate Predictions
hopefully
Fine-tuning?
adjusting weights to minimize error
Bird or Not
What would be the Machine Learning approach?
What would be the Deep Learning approach?
Training
vs
Inference
Training
Training is the process of teaching the model using historical data, adjusting weights to minimize error
What would training look like for
"Bird or Not"
Inference
Inference is using the trained model to make predictions on new data.
What is used in production?
Homework
